PART V

Tools and Techniques

This part of the book presents a collection of additional Python application topics.

Most of the tools presented along the way can be used in a wide variety of application

domains. You’ll find the following chapters here:

Chapter 17

This chapter covers commonly used and advanced Python techniques for storing

information between program executions—DBM files, object pickling, object

shelves, and Python’s SQL database API—and briefly introduces full-blown

OODBs such as ZODB, as well as ORMs such as SQLObject and SQLAlchemy.

The Python standard library’s SQLite support is used for the SQL examples, but

the API is portable to enterprise-level systems such as MySQL.

Chapter 18

This chapter explores techniques for implementing more advanced data structures

in Python—stacks, sets, binary search trees, graphs, and the like. In Python, these

take the form of object implementations.

Chapter 19

This chapter addresses Python tools and techniques for parsing text-based infor-

mation—string splits and joins, regular expression matching, XML parsing, re-

cursive descent parsing, and more advanced language-based topics.

Chapter 20

This chapter introduces integration techniques—both extending Python with

compiled libraries and embedding Python code in other applications. While the

main focus here is on linking Python with compiled C code, we’ll also investigate

integration with Java, .NET, and more. This chapter assumes that you know how

to read C programs, and it is intended mostly for developers responsible for im-

plementing application integration layers.

This is the last technical part of the book, and it makes heavy use of tools presented

earlier in the text to help underscore the notion of code reuse. For instance, a calculator

GUI (PyCalc) serves to demonstrate language processing and code reuse concepts.

Do

wnload from Wow! eBook <www.wowebook.com>